October 4, 2022

oumiss

Forget Mediocre Fashion

Best Practices for Monitoring Data

Lulu Suds gift set

managing databy Sean Kantor and Elay Talmor

In April 2021, iOS released a major privacy update which gave users tremendously more transparency and control over how brands track them for advertising purposes. Overnight, this massive change forced brands to overhaul their strategy of how they are using outside platforms and how much they can rely on them for accurate information. 

The change resulted in brands losing connection with users, as well as the ability to effectively target potential customers when advertising on iOS platforms. All in all, brands were forced to make drastic changes overnight to their online marketing efforts. One of the biggest changes impacted how brands attribute sales to clients and how to accurately anticipate which platforms are effectively bringing in the most users.

Utilizing Predictive Analytics

Since the privacy update, there have been many important missing pieces of information in the user’s journey, and data teams need to find their own solutions to fill this data gap. Brands need to invest in building their own algorithms, statistics, and solutions to effectively track users entering their site, but this data is not always strong enough. This is where predictive analytics come in as a solution, a tactic that can help brands more accurately gauge a customer’s journey on a website.

Every platform uses a different attribution system, so it is essential to invest in testing new statistical models, rely on more first party data, and to develop innovative solutions around finding new ways to track users when they enter a site. Brands should focus on creating a more holistic understanding on measuring customer behavior in order to be successful.

Reviewing Data from Different Platforms

Data teams need to think about ways to verify that external platform data is accurate, as platforms want to take credit for sales. If a brand deems that a certain platform is helping conversion, then they will continue to invest more money into the platform, but brands need to think about how much of the sale is being pushed from a certain platform and how much is coming from the brand itself. Brands need to constantly assess what the perfect combination is that leads to a conversion, and the perfect balance between what platforms to push. When looking at each platform, it is important to recreate how to use data, and to look at multiple platforms as one long funnel to better understand the entire funnel.

Now is truly the age of privacy, and it is only a matter of time before top companies will start following suit. Data teams should be focused on thinking about what the future of performance marketing is and anticipate the next change that will affect their strategy. Privacy changes will continue to change and evolve, and data teams should determine how to stay ahead of the curve and be prepared for the upcoming adjustments. We are currently in an age of over information and it is impossible to analyze all the data and information we have, so we need to be selective about where we spend our resources and what information can most effectively help us to better understand and track our customers, in order to provide the best shopping experience possible.

Create a Structure for Analyzing Data

Seemingly overnight, Apple completely changed the way the entire world digitally marketed their customers. This massive change completely transformed the way we approach clients and now it is essential for companies to rely on their own data and systems for performance. Platform data should be used strictly for what companies cannot do themselves. It is imperative to think ahead and create a structure for how we analyze platform data and ads, so it is easy to make quick decisions and changes, attribute data, and improve day-to-day. Platforms need to add more options for cross platform reporting and give the option to predict sales from each ad via predictive analytics. The future is green and the most important thing is to find the most efficient way to be reactive to our own data.

Written by Sean Kantor (Director of Marketing Analytics), and Elay Talmor (Web & Data Analyst) at GlassesUSA.com, a leading online optical retailer using data and technology to enhance the lives of their customers by providing the perfect pair of glasses individually catered to every person’s unique style, budget, and exact needs.